Resource Provisioning for CPU-FPGA Environments with Adaptive HLS-Versioning and DVFS

M. Jordan, Guilherme Korol, Tiago Knorst, M. B. Rutzig, A. C. S. Beck
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Abstract

Cloud warehouses have been adopting CPU-FPGA environments to accelerate clients’ applications with scalability. On the CPU side, DVFS improves energy efficiency. On the FPGA side, High-Level Synthesis enables hardware optimizations that lead to designs with variant characteristics (e.g., latency and power). Although both techniques have been used, they have never been cooperatively exploited to improve execution efficiency. For that, we propose RAHD, a framework that bridges the gap between DVFS, HLS multiple design versions, and CPU-FPGA environments. RAHD offers automatic fine-tuning selection of design versions and DVFS to efficiently balance workload, achieving 32.86x energy improvements over a standard provisioning strategy.
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基于自适应hls版本控制和DVFS的CPU-FPGA环境资源配置
云仓库一直在采用CPU-FPGA环境来加速客户端应用程序的可伸缩性。在CPU方面,DVFS提高了能源效率。在FPGA方面,高级综合实现了硬件优化,导致设计具有不同的特性(例如,延迟和功耗)。虽然使用了这两种技术,但它们从未被合作地利用来提高执行效率。为此,我们提出RAHD,这是一个在DVFS、HLS多设计版本和CPU-FPGA环境之间架起桥梁的框架。RAHD提供自动微调选择设计版本和DVFS,以有效地平衡工作负载,实现比标准配置策略32.86倍的能源改进。
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